<p> One of the important objectives of a Radar Warning Receiver (RWR) aboard a
tactical aircraft is to evaluate the level of threat posed by hostile radars in an extremely
complex Electronic Warfare (EW) environment in reliable, robust and
timely manner. For the RWR objective to be achieved, it passively collects electromagnetic
signals emitted from potentially hostile radars. One class of such
radar systems is the Multi-Function Radar (MFR) which presents a serious threat
from the stand point of a RWR. MFRs perform multiple functions simultaneously
employing complex hierarchical signal architecture. The purpose of this paper is
to uncover the evolution of the operational mode (radar function) from the view
point of a target carrying the RWR when provided with noisy observations and
some prior knowledge about how the observed radar functions. The RWR estimates
the radar's threat which is directly dependant on its current mode of operation.
This paper presents a grid filter approach to estimate operational mode
probabilities accurately with the aid of pre-trained Observable Operator Models
(OOMs) and Hidden Markov Models (HMMs). Subsequently, the current mode
of operation of a radar is estimated in the maximum a posteriori (MAP) sense.
Practicality of this novel approach is tested for an EW scenario in this paper by
means of a hypothetical MFR example. Finally, we conclude that the OOM-based
grid filter tracks the mode of operation of a MFR more accurately than the corresponding
HMM-based grid filter. </p> / Thesis / Master of Applied Science (MASc)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/21876 |
| Date | 02 1900 |
| Creators | Arasaratnam, I |
| Contributors | Haykin, Simon, Kirubarajan, Thia, Electrical Engineering |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
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